DataVisor

Real-time fraud detection & risk management

Senior Infrastructure Engineer

Platform Engineering +1Posted on Nov 13

Full-timeRemote in CanadaCA$120k - CA$150k /yrRemote

About the Job

Requirements

At least 5 years of experience in infrastructure, site reliability engineering, DevOps, or platform engineering on production systems.
Hands-on experience running Kubernetes in production.
Strong AWS experience and infrastructure-as-code experience with Terraform or CloudFormation.
Monitoring, alerting, and on-call experience with Prometheus/Grafana or similar tools.
Solid programming skills in Java, Go, or Python, with experience shipping production code, not only scripts.
Experience running at least one distributed data system: Kafka, Flink, Spark, ClickHouse, or MySQL.
A degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience.

Responsibilities

Design, operate, and scale Kubernetes (EKS) clusters for multi-tenant and customer-dedicated deployments, including Helm, upgrades, autoscaling, and troubleshooting.
Build AWS infrastructure as code with Terraform (VPC, IAM, EC2, EKS, S3) and keep environments reproducible.
Run and tune the data systems that detection depends on—Kafka, Flink, Spark, ClickHouse, and MySQL—covering capacity, performance, and reliability.
Own observability with Prometheus, Grafana, and Loki; define SLOs, lead incident response, and run on-call.
Develop production software in Java, Go, or Python, including platform services, internal tools, deployment automation, and CI/CD pipelines.
Help design distributed real-time systems with the platform team for low-latency decisioning at scale.
Lead security and reliability practices, including access control, secrets, backups, disaster recovery, and SOC 2 / PCI controls.
Drive cloud cost optimization across compute and big-data workloads.
Mentor junior engineers and set infrastructure standards.

Desired Qualifications

Experience with fraud, risk, payments, or banking infrastructure; SOC 2 or PCI environments.
Experience with low-latency streaming or real-time decisioning platforms.
Experience with multi-region, multi-tenant, or customer-hosted (private) SaaS deployments.
FinOps or cloud cost reduction with measurable results.
Internal tooling built with LLMs, or AI-assisted operations.

Senior Infrastructure Engineer - Toronto

DataVisor · Toronto, Canada (Remote) · Full-time · Posted 2026-11-13

Salary: CAD 120,000–150,000

Workplace: remote

Department: Engineering

Description

About DataVisor

DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Role Overview

Our infrastructure team runs the platform that makes real-time fraud detection possible, and writes much of the software that runs on it. You will own production infrastructure end to end: Kubernetes clusters on AWS, the streaming and data systems behind detection, and the tools and services that keep them reliable. You will also design and build backend and platform code alongside the engineering teams.

Requirements

What you'll do

Design, operate and scale Kubernetes (EKS) clusters for multi-tenant and customer-dedicated deployments: Helm, upgrades, autoscaling, troubleshooting.
Build AWS infrastructure as code with Terraform (VPC, IAM, EC2, EKS, S3) and keep environments reproducible.
Run and tune the data systems detection depends on: Kafka, Flink, Spark, ClickHouse and MySQL, covering capacity, performance and reliability.
Own observability with Prometheus, Grafana and Loki. Define SLOs, lead incident response and run on-call.
Develop production software in Java, Go or Python: platform services, internal tools, deployment automation and CI/CD pipelines.
Help design distributed real-time systems with the platform team, for low-latency decisioning at scale.
Lead security and reliability practices: access control, secrets, backups, disaster recovery, and SOC 2 / PCI controls.
Drive cloud cost optimization across compute and big-data workloads.
Mentor junior engineers and set infrastructure standards.

What you'll bring

5+ years in infrastructure, SRE, DevOps or platform engineering on production systems.
Hands-on experience running Kubernetes in production.
Strong AWS experience and infrastructure as code (Terraform or CloudFormation).
Monitoring, alerting and on-call experience with Prometheus/Grafana or similar tools.
Solid programming skills in Java, Go or Python, with experience shipping production code, not only scripts.
Experience running at least one distributed data system (Kafka, Flink, Spark, ClickHouse or MySQL).
A degree in Computer Science, Computer Engineering, Electrical Engineering or a related field, or equivalent experience.

Nice to have

Fraud, risk, payments or banking infrastructure; SOC 2 or PCI environments.
Low-latency streaming or real-time decisioning platforms.
Multi-region, multi-tenant or customer-hosted (private) SaaS deployments.
FinOps or cloud cost reduction with measurable results.
Internal tooling built with LLMs, or AI-assisted operations.

Benefits

Compensation: Annual salary range of CAD $120,000 – $150,000, commensurate with experience.
Health Insurance, including (Extended Health Care, Vision Care, and Dental Care)
Life Insurance, Accidental Insurance
Retirement Savings Plan
Paid Vacation

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About the Company

DataVisor

Real-time fraud detection & risk management

DataVisor offers a fraud detection and risk management platform for fintech and cybersecurity, helping financial institutions, e-commerce platforms, and online services detect and prevent fraudulent activity in real time. The core product integrates with clients’ existing data systems through APIs, supporting real-time or batch data processing to identify suspicious patterns. Machine learning analyzes large datasets to spot indicators of fraud and continuously improve detection accuracy. The company differentiates itself by providing a flexible, API-based integration that fits into clients’ current workflows and data environments, enabling real-time prevention across diverse use cases. Revenue comes from a subscription model that gives clients ongoing access to the platform and updates. The goal is to help organizations protect their operations and customers by staying ahead of increasingly sophisticated fraud schemes.

Company size: 51-200
Company stage: Late Stage VC
Total funding: $94.5M
Headquarters: Mountain View, CA
Founded: 2013

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